Educating students on the behavioral and psychological aspects of romance scam victimization via a social engineering competition

Bleiman, Rachel ; Park, Hwanhee ; Rege, Aunshul (2025) — Journal of Cybersecurity Education, Research and Practice

Synopsis (AI-Generated)

The online dating sector generated 2.98 billion USD in 2023 and is projected to reach about 3.6 billion USD by 2025. Within this space, romance scams impose substantial financial losses, estimated at 1.3 billion USD in 2022, and they also inflict emotional and psychological harm on those affected. The article reports on findings from a 2023 Romance Scam and Social Engineering Competition (RSSEC), which introduced students to the behavioral and psychological dimensions of romance fraud and its broader implications for cybersecurity and victim safety. The competition was designed to illuminate how victims experience social engineering across the stages of a romance scam and to place participants in dual roles: as fraud fighters who interact with victims with respect and empathy, and as observers of scammers who rely on social engineering tricks. The paper details the design of the event, including elements that incorporated artificial intelligence, along with its overall structure and logistical setup. It also shares insights into what students learned about the use of psychological persuasion to manipulate victims during the scam process and about their capacity to collaborate effectively as defenders against fraud. Findings show that participants developed a clearer understanding of how psychological persuasion operates within romance scams and demonstrated the ability to work cohesively as a team of fraud fighters. The RSSEC afforded students the opportunity to treat scam victims with dignity by applying tactical empathy, a key capability for appreciating the behavioral and psychological aspects involved in cybercrime victimization. Overall, the study highlights how experiential competition formats can advance awareness of social engineering tactics and promote ethical, victim-centered responses among future professionals in the field.

Identified Gaps (AI-Generated)

The paper identifies a lack of experiential-learning resources focused specifically on social engineering that do not require technical knowledge or prerequisites. Existing cybersecurity experiential learning opportunities tend to emphasize technical cybersecurity while only partially addressing social engineering. The authors position the romance-scam competition as a hands-on educational resource intended to address this gap.

Methods (AI-Generated)

The study reports findings from a virtual, three-day 2023 Romance Scam and Social Engineering Competition involving 16 student teams across high-school, undergraduate, and graduate tracks. Teams investigated a simulated elderly romance-scam victim, interacted with simulated friends, victim, and scammer, analyzed persuasion tactics and evidence, and delivered an empathetic debrief and victim checklist. The scenario used AI-generated visual material. Participant demographics, pre/post confidence, and feedback on task difficulty, preparation, teamwork, and relevance were collected and summarized.

Limitations (AI-Generated)

The competition used one simulated romance-scam case and therefore captured only a cross-section of possible romance-scam manifestations. The authors state that the scenario is not generalizable to all romance scams, does not comprehensively represent scams across multiple platforms, and cannot capture every nuance or the full range of scam possibilities. Findings concern a focused student learning opportunity rather than actual victim experiences or a comprehensive account of romance fraud.

Future Work (AI-Generated)

Future competitions or research should examine different variations of romance scams and other scams, involve participants beyond students, and assess the competition’s long-term effects on students’ professional practices or attitudes. The authors also plan to use AI in future competition design and live engagements, including education about AI-enabled social engineering such as voice cloning in vishing.

AI-Generated Content Notice

The synopsis and research notes on this page were generated with AI from available publication information and, when available, the uploaded paper text. They may contain errors, omissions, or interpretation issues. Readers should follow the DOI or source link, review the original publication, and make their own judgment about the content.

Found a possible error? Request a correction.